The field of the invention is methods of computer analysis for forewarning of condition changes, including critical events, such as epileptic seizures in human medical patients, and including failures in machines and other physical processes.
Hively et al., U.S. Pat. Nos. 5,743,860 and 5,857,978 disclose methods for detecting and predicting epileptic seizures by acquiring brain wave data from a patient, and analyzing the data with traditional nonlinear methods.
Hively et al., U.S. Pat. No. 5,815,413, disclosed the use of phase space dissimilarity measures (PSDM) to forewarn of impending epileptic events from scalp EEG in ambulatory settings. Hively et al., U.S. Pat. No. 5,815,413, also discloses the applicability of nonlinear techniques to monitor machine conditions such as the condition of a drill bit or the performance of an electrical motor driving a pump.
Hively, U.S. Pat. No. 7,139,677, introduced a composite measure of dissimilarity (C). This composite measure of condition change (C) was calculated from the sum of the four normalized measures of dissimilarity, including U(χC2) and U(LC) from the connected phase space and including U(χN2) and U(LN) from the non-connected phase space. This was developed further across multiple data channels in Hively, U.S. Pat. No. 7,209,861, where the composite measure of dissimilarity, (C), was used to provide an end-of-life forewarning factor (G).